Deciphering the language of fungal pathogen recognition receptors - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2015

Deciphering the language of fungal pathogen recognition receptors


The NLR family of receptors plays a key role in the innate immune system of animals, plants and fungi. In the latter two phyla NLRs adapt quickly to ever-changing pathogen-specific invasion markers thanks to their repeat-based architecture, which can produce diversity of recognition epitopes through unequal crossing-over and mutation. Characterizing computationally the language of these pathogen recognition receptors can provide insight into the molecular mechanisms of immune response and describe the limits of the pathogen targets that can be recognized. In this work, we model generation and selection of the recognition epitopes as a stochastic string rewriting system with constraints, tuned by analysis of observed evolutionary processes and validated with regard to a large dataset of fungal NLRs. Among others, analyzing the feasible set of solutions revealed that the model explained the i/i + 2 periodicity observed in the repeat number distribution of a family of receptors. In addition, in exploring discrepancies between real and simulated data we discovered an overrepresented pattern which potentially has functional importance.
Fichier principal
Vignette du fichier
wdyrka_emboysf2015.pdf (1.9 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01171745 , version 1 (06-07-2015)


  • HAL Id : hal-01171745 , version 1


Witold Dyrka, Pascal Durrens, Sven J Saupe, Mathieu Paoletti, David James Sherman. Deciphering the language of fungal pathogen recognition receptors. EMBO Young Scientists Forum 2015, Jul 2015, Warsaw, Poland. , 2015. ⟨hal-01171745⟩
191 View
76 Download


Gmail Facebook Twitter LinkedIn More